Raul is a serial entrepreneur. He has created four companies in different fields in the mobile robotics space for warehouse automation and autonomous driving 3D perception. He has hired 200+ people and raised over $125 million including an IPO.
He worked with Cédric Hutchings, Outsight co-founder, at Inventel as a Program Manager, leading strategic projects that grew from the concept-phase to mass-production in several months. Following this, Raul co-founded and led Balyo (Mobile Robotics pioneer for logistics) from 2004 and left in 2017 after the IPO in order to focus on its newly created company Dibotics, the creator of the Augmented LiDAR and the world-first SLAM-on-Chip technology.
He received his degree in engineering from UPC (Barcelona, Spain) and MBA from College des Ingénieurs (Paris, France). Raul has obtained 35 different awards for his engineering and entrepreneur career, among them as best Spanish Engineer and the MIT Technology Review – Top 10 Innovators Under 35 and filed 31 patents.
He has been invited to speak at major Autonomous Driving and Robotics events such as AutoSens, IS Auto, ADAS Sensors, Automotive LiDAR conference, Autonomous Car Software Symposium, Cognitive Vehicles, Off-Road Autonomous Vehicles and many more.
We define Situation Awareness by the ability to simultaneously perform Perception, Localisation and Comprehension of the environment.This ability is fundamental to any Smart Machine such as a self-driving car: it is a prerequisite to take action in the real world. The initial approach of the industry to solve this key challenge has been to increase the capabilities of separated sensors like LiDAR, Cameras, Radar, IMUs; combine them via Sensor Fusion and process the resulting data using Machine Learning (ML) on powerful computing platforms. However, the Scalability and Reliability levels required for mass-produced Smart Machines can’t be achieved without solving the new challenges that this approach creates, including the problems of Calibration, Synchronisation, Latency, Energy consumption, Cost and “explainability”. We will introduce in the presentation a new technical solution and the working principles of its main components: The combination of a novel broadband laser imager with an innovative processing approach that allows for an industry’s first real-time Full Situation Awareness in a standalone device, including the identification of the Material composition of objects (Skin, plastic, metal...) We'll explore how this new technology will not only accelerate the emergence of fully automated Smart Machines like L4-L5 Self-Driving Cars, Robots, and Autonomous Flying Taxis but will also bring the safety benefits of Full Situation Awareness to the current man-controlled machines like L1-L3 ADAS (Advanced Driving Assistance Systems), Construction/Mining equipment, Helicopters and many more.